Faculty.ai Interview Questions
The questions to prepare for Faculty.ai interviews, across all roles. Questions from real interview reports rank first. Updated daily.
Identify the main pitfalls that can distort A/B test interpretation and explain how to guard against them.
Sign up to see every question
Create a free account to unlock this list and practice real interview questions.
Outline the first checks to diagnose a sudden drop in a core product metric, starting with data quality, scope, and decomposition.
Approach for handling missing data in an ML data pipeline, including validation, imputation, and safe downstream consumption.
Explain which classification metrics to use and how metric choice depends on the business objective and error tradeoffs.
Explain how the bias-variance tradeoff guides algorithm selection and generalization performance.
Analyze Spark query runs, identify bottleneck stages, and flag performance regressions using PostgreSQL SQL.
DatabricksFramework for choosing a feature's primary success metric and guardrails before launch.
Explain how to calculate cumulative totals in SQL using window functions, ordering, and optional pre-aggregation.
Calculate per-user engagement totals and active days over inclusive rolling 30-day windows using PostgreSQL window functions.
Xero
HudlCount valid daily interactions and return the top three users using aggregation and deterministic ranking.